AI Engineer - Global Strategy Consultant

AI Engineer - Global Strategy Consultant

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Transform AI prototypes into enterprise-ready tools and applications.
  • Company: Join Accenture, a global leader in professional services and innovation.
  • Benefits: Enjoy competitive pay, diverse culture, and opportunities for growth.
  • Other info: Collaborate closely with experts in a small, hands-on team environment.
  • Why this job: Make a real impact with cutting-edge AI technology in a dynamic team.
  • Qualifications: Degree in relevant field and experience in client-facing technical roles.

The predicted salary is between 60000 - 80000 £ per year.

Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual, and Integrity.

QuantAI is building cutting-edge AI-native decision-system assets for energy, commodities, financial, trading, and industrial operations. We are looking for engineers who can take strong quantitative and artificial intelligence (AI) work and turn it into enterprise-safe products: interfaces, packaged desktop applications, APIs, services, workflow systems, and demos that are credible enough for pilots and durable enough for scaled delivery.

Success here is not raw model novelty or polished demos in isolation. It is strong algorithms wrapped in workflow, governance, evaluation, and packaging. This role is engineer-first and shipping-first. The engineering covers two surfaces that both ship as product: conventional systems on one side, agent-assisted systems on the other. The team is too small for either to be someone else’s problem, and you should be able to operate across both—though you will likely lead with strength in one.

What you'd work on:

  • Turn quantitative prototypes into reusable tools, services, packaged desktop applications, interfaces, and workflow products that can move from internal demo to client pilot to scaled offer.
  • Ship across both cloud-hosted services and locally distributed desktop applications, including Electron-based apps when the workflow or client environment calls for it.
  • Build enterprise hardening into the productization layer, including authentication, role-based access control (RBAC), observability, security, release quality, cost controls, and deployment discipline.
  • Build evaluation, regression, and release discipline into the productization layer so model logic and agent behavior remain measurable as systems change.
  • Work closely with the quant lead so model logic, evaluation intent, and governance requirements survive the move into production.
  • Make pragmatic architecture choices across large language models (LLMs), deterministic rules, and hybrid systems based on value, latency, cost, and reliability.
  • Help shape repeatable build patterns so strong prototypes become faster, more reliable, and more reusable over time.

Platforms and interfaces:

  • Own data flows, APIs, services, model-serving surfaces, front-end and desktop application surfaces, CI/CD, and demo hardening.
  • Build the systems that make quantitative work feel polished, reliable, and enterprise-ready for expert users and client stakeholders.

Agent-assisted systems:

  • Own the agentic harness layer — evaluation frameworks, reviewer loops, control-plane behavior, orchestration, and tool integration — that applications and MCPs wrap around.
  • Design opinionated harnesses that expose through MCP or similar integration patterns without overfitting to one vendor or one moment in the tooling market.

Must-have:

  • Bachelor's degree in computer science, engineering, mathematics, physics, economics, or a related field. An associate degree is acceptable with at least 2 additional years of directly relevant experience and evidence of shipped engineering work.
  • Minimum 3 years of experience in consulting or other client-facing technical delivery roles, with evidence of moving products, internal tools, or workflow systems beyond proof-of-concept.
  • Minimum 3 years of hands-on experience in one or more of: backend services, APIs and integrations, full-stack delivery, data pipelines, model-serving or machine learning workflows, or agentic orchestration systems.
  • Strong coding ability in Python plus one complementary engineering surface such as TypeScript or JavaScript, front-end delivery, cloud or platform engineering, or infrastructure automation.
  • Experience with enterprise hardening and evaluation, including authentication, RBAC, observability, security, release discipline, regression testing, or experiment frameworks for AI/machine learning/agentic workflows.

Nice-to-have:

  • Experience with tool-using systems, retrieval, evaluation pipelines, agent orchestration, or MCP-style integrations.
  • Experience building expert-facing interfaces, workflow products, or technical demos for real users.
  • Experience packaging desktop applications or supporting Windows-heavy enterprise environments.
  • Exposure to forecasting, anomaly detection, optimization, time-series workflows, or other decision-support tasks.
  • Experience in energy, commodities, financial, trading, market operations, or industrial workflows.

Team and environment:

QuantAI sits between quantitative research, agentic engineering, and product delivery inside Accenture. The team is small, hands-on, and built for people who want visible ownership and the chance to build something lasting. The goal is reusable assets clients can trust, buy, and scale. Direct technical feedback, growing scope, and close collaboration with quants and practice leadership are expected. This is a small-team build environment with real route-to-market access in energy, commodities, financial, trading, and industrial decision systems. The work needs to stand up in front of business decision makers and operators, not just engineers.

Equal Employment Opportunity:

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. Bring your incredible skills and join our global team of innovators.

About Accenture:

Accenture is a leading global professional services company that helps the worlds leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the worlds leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

AI Engineer - Global Strategy Consultant employer: 3003 Accenture (UK) Limited Company

Accenture is an exceptional employer, offering a dynamic work environment in London where innovation and collaboration thrive. With a strong commitment to inclusion and diversity, employees benefit from continuous growth opportunities and the chance to work on cutting-edge AI projects that have a real impact on global industries. The culture fosters ownership and creativity, making it an ideal place for those looking to make meaningful contributions while advancing their careers.

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Contact Details:

3003 Accenture (UK) Limited Company Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Engineer - Global Strategy Consultant

Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Accenture. A friendly chat can sometimes lead to job opportunities that aren't even advertised.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and engineering. Having tangible examples of your work can really impress potential employers during interviews.

Tip Number 3

Prepare for technical interviews by brushing up on your coding skills and understanding AI concepts. Practice common interview questions and consider mock interviews to build your confidence.

Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the team at Accenture.

We think you need these skills to ace AI Engineer - Global Strategy Consultant

Quantitative Analysis
Artificial Intelligence (AI)
Backend Services
APIs and Integrations
Full-Stack Delivery
Data Pipelines
Machine Learning Workflows

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the AI Engineer role. Highlight your relevant experience in consulting, coding skills, and any projects that showcase your ability to turn prototypes into enterprise-ready products.

Showcase Your Technical Skills:We want to see your coding prowess! Include specific examples of your work with Python, TypeScript, or JavaScript, and any hands-on experience with APIs, data pipelines, or machine learning workflows. This is your chance to shine!

Demonstrate Your Problem-Solving Ability:In your application, share instances where you've tackled complex challenges in a client-facing role. We love seeing how you’ve turned quantitative work into practical solutions that clients can trust and scale.

Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensure you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!

How to prepare for a job interview at 3003 Accenture (UK) Limited Company

Know Your Tech Inside Out

Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and any complementary languages like TypeScript or JavaScript. Brush up on your experience with APIs, backend services, and machine learning workflows, as these will likely come up during technical discussions.

Showcase Your Problem-Solving Skills

Prepare to discuss specific examples where you've turned quantitative prototypes into reusable tools or services. Be ready to explain your thought process and the impact of your work, especially in client-facing roles. This will demonstrate your ability to deliver real value.

Understand the Business Context

Familiarise yourself with the industries Accenture operates in, such as energy, commodities, and financial services. Understanding the business challenges these sectors face will help you tailor your responses and show that you can apply your technical skills to solve real-world problems.

Emphasise Collaboration and Communication

Since this role involves working closely with quants and other stakeholders, be prepared to discuss how you’ve successfully collaborated in the past. Highlight your communication skills and how you ensure that technical concepts are understood by non-technical team members or clients.